AI and Performance Support Add Up to Intuitive Assistance

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May 14, 2018

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Discussions of whether or how artificial intelligence (AI) will affect eLearning and performance support miss a key fact: AI already is part of eLearning and performance support tools. AI is an enormous umbrella, and the technologies that are collectively referred to as AI are constantly changing and expanding. Here’s a brief look at AI and performance support—some surprising places it already crops up, and some future trends to watch.

AI powers performance support tools

Many managers, executives, developers, and even eLearning designers dread writing. They fear being judged for their errors, or they rely on spelling- and grammar-checking tools to add polish to their quickly jotted (or laboriously typed) documents. But plain old spelling checkers went out with the twentieth century. Modern tools—Grammarly is one example—do much more than help writers avoid errors in a word processing tool. They catch errors across a wider variety of tools, and they harness AI engines to notice other errors that a spelling checker would glide right over. While editors can—and do—debate the value of these tools and bemoan their propensity to introduce errors in some cases, the bottom line is that not all written materials receive the attention of a copy editor. Performance support tools can put AI engines to work to provide in-the-moment help and improve the performance of countless corporate learners.

Chatbot-based mobile performance support is another area where improvements in AI drive the development of better and more natural job aids. For a few years already, chatbot-based tools have been conducting text-based conversations to quiz learners on material covered in a training course or refresh their memories of material covered elsewhere. Those tools can also offer prompts for more reflective questions that learners might discuss with colleagues in a learning cohort or with their managers.

But progress marches on. Natural language processing abilities in AI-based eLearning tools now enable learners to “converse” with these performance support tools in a way that feels (almost) like talking with a human. The applications for this range from assessment testing and drilling of skills and concepts to more natural searches for information, answers to questions, and suitable learning materials within a library of curated or L&D-generated eLearning content. Interactions might take place via text chat or using voice recognition. AI algorithms are constantly improving in their ability to recognize a variety of speech patterns, accents, dialects, and inflections. This can be a boon to learners with disabilities, who will experience fewer barriers to their access to online content, eLearning, and performance support tools.

Natural language skills can enhance performance support tools in a variety of ways, whether they’re used to understand learners’ speech or text or to generating content or responses to those learners. What’s more, AI-based tools can sift through enormous amounts of content or data very quickly, which means they can find content, determine what content is related or relevant, and tailor their responses to each learner’s questions and performance.

Mind-reading computers?

Future tools might become even more intuitive. A recent 60 Minutes segment featured Arnav Kapur, a researcher at the MIT Media Lab who is developing software that can intercept the signals that his brain sends out when he thinks in words—and send it to his computer as the input for a Google search. The interviewer asked him a question; he (supposedly) thought the question, and, within a few seconds, the question and an answer appeared on a nearby computer screen.

While the creepiness factor is high, this is an example of one type of ambient interface, what the 2018 Tech Trends report from the Future Today Institute calls “auto-complete for intention.” The Report says that these interfaces will collect information from us, both actively and passively. We can speak to them, as we might speak to a digital assistant. They will also “listen and observe in the background, sometimes asking questions—other times offering up text, audio, or haptic notifications as needed, and those will be decided by algorithm.”

The effects on eLearning and performance support are likely to be felt primarily in greater automation and greater personalization of content and tools. The Tech Trends Report also anticipates increased use and availability of digital assistants—with ambient interfaces. With the ability to “intuit” a person’s needs and anticipate decisions, an ever-accessible digital assistant could schedule the person’s appointments, let people know when she’s running late, remind her of upcoming obligations, order office supplies, even adjust the temperature in her home or office before she arrives and order her lunch. While none of those tasks are conventional “performance support,” an intuitive digital assistant would enable workers and managers to glide smoothly through the day without having to keep track of myriad details and deal with routine tasks. As a result, those workers would be more focused on their work and on bigger decisions: Thus their performance could improve dramatically.

The bottom line is that AI and performance support are a formidable combination that could result in personalized, intuitive tools that drive performance of individuals and teams to new levels of efficiency.

AI and Performance Support Add Up to Intuitive Assistance

Topics

Discussions of whether or how artificial intelligence (AI) will affect eLearning and performance support miss a key fact: AI already is part of eLearning and performance support tools. AI is an enormous umbrella, and the technologies that are collectively referred to as AI are constantly changing and expanding. Here’s a brief look at AI and performance support—some surprising places it already crops up, and some future trends to watch.

AI powers performance support tools

Many managers, executives, developers, and even eLearning designers dread writing. They fear being judged for their errors, or they rely on spelling- and grammar-checking tools to add polish to their quickly jotted (or laboriously typed) documents. But plain old spelling checkers went out with the twentieth century. Modern tools—Grammarly is one example—do much more than help writers avoid errors in a word processing tool. They catch errors across a wider variety of tools, and they harness AI engines to notice other errors that a spelling checker would glide right over. While editors can—and do—debate the value of these tools and bemoan their propensity to introduce errors in some cases, the bottom line is that not all written materials receive the attention of a copy editor. Performance support tools can put AI engines to work to provide in-the-moment help and improve the performance of countless corporate learners.

Chatbot-based mobile performance support is another area where improvements in AI drive the development of better and more natural job aids. For a few years already, chatbot-based tools have been conducting text-based conversations to quiz learners on material covered in a training course or refresh their memories of material covered elsewhere. Those tools can also offer prompts for more reflective questions that learners might discuss with colleagues in a learning cohort or with their managers.

But progress marches on. Natural language processing abilities in AI-based eLearning tools now enable learners to “converse” with these performance support tools in a way that feels (almost) like talking with a human. The applications for this range from assessment testing and drilling of skills and concepts to more natural searches for information, answers to questions, and suitable learning materials within a library of curated or L&D-generated eLearning content. Interactions might take place via text chat or using voice recognition. AI algorithms are constantly improving in their ability to recognize a variety of speech patterns, accents, dialects, and inflections. This can be a boon to learners with disabilities, who will experience fewer barriers to their access to online content, eLearning, and performance support tools.

Natural language skills can enhance performance support tools in a variety of ways, whether they’re used to understand learners’ speech or text or to generating content or responses to those learners. What’s more, AI-based tools can sift through enormous amounts of content or data very quickly, which means they can find content, determine what content is related or relevant, and tailor their responses to each learner’s questions and performance.

Mind-reading computers?

Future tools might become even more intuitive. A recent 60 Minutes segment featured Arnav Kapur, a researcher at the MIT Media Lab who is developing software that can intercept the signals that his brain sends out when he thinks in words—and send it to his computer as the input for a Google search. The interviewer asked him a question; he (supposedly) thought the question, and, within a few seconds, the question and an answer appeared on a nearby computer screen.

While the creepiness factor is high, this is an example of one type of ambient interface, what the 2018 Tech Trends report from the Future Today Institute calls “auto-complete for intention.” The Report says that these interfaces will collect information from us, both actively and passively. We can speak to them, as we might speak to a digital assistant. They will also “listen and observe in the background, sometimes asking questions—other times offering up text, audio, or haptic notifications as needed, and those will be decided by algorithm.”

The effects on eLearning and performance support are likely to be felt primarily in greater automation and greater personalization of content and tools. The Tech Trends Report also anticipates increased use and availability of digital assistants—with ambient interfaces. With the ability to “intuit” a person’s needs and anticipate decisions, an ever-accessible digital assistant could schedule the person’s appointments, let people know when she’s running late, remind her of upcoming obligations, order office supplies, even adjust the temperature in her home or office before she arrives and order her lunch. While none of those tasks are conventional “performance support,” an intuitive digital assistant would enable workers and managers to glide smoothly through the day without having to keep track of myriad details and deal with routine tasks. As a result, those workers would be more focused on their work and on bigger decisions: Thus their performance could improve dramatically.

The bottom line is that AI and performance support are a formidable combination that could result in personalized, intuitive tools that drive performance of individuals and teams to new levels of efficiency.

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